IDE with Improved GUI for Best Usability
HALCON's unique IDE (integrated development environment) for machine vision, HDevelop and HDevEngine, has been radically improved in design and functionality. The HDevelop GUI has been modernized and now is available in many common languages. Furthermore, HDevelop provides new assistants to greatly simplify the generation of frequently used operator sequences.
HDevelop now with syntax highlighting, integrated online help, and many more new features.
3D Object Recognition
You need no specialized imaging software to enter the world of 3D, e.g., for bin picking and other robot tasks. With HALCON 8.0, 3D matching now can be done with a machine vision standard software: 3D matching finds objects in arbitrary 3D poses based on a CAD model with the same power and robustness as HALCON's well-known shape-based matching. To identify an object from its CAD model, only one image taken by a single camera is necessary. CAD models can be read in DXF format.
Shape-based Matching in Color Images, Correlation-based Matching
HALCON's robust methods for matching have been further improved. Shape-based matching now also handles objects with different scaling in row and column as well as objects that are partially located outside of the image. Further, it can process images with 8 or 16 bits and handles also color or multi-channel images. Correlation-based matching is particularly robust against defocus, shape deformation, and texture.
A Library Faster than the State of the Art
The speed of the entire HALCON software library has been significantly enhanced, on average by 25 %, single operators by up to 500% for typical applications. This speedup is achieved by an advanced memory management as well as an extended use of MMX and SSE2, and many more improvements of the HALCON core. Also the performance on multi-core processors has been substantially improved by optimizing Parallel HALCON 8.0.
Easy-to-Use OCR with Auto-Correction
HALCON's powerful classifiers have been enhanced and optimized for usability. They lead to highest recognition rates "out of the box", such as 0.65 % error rate on the image set of MNIST standard. Additionally, HALCON provides a syntactic and lexicon-based auto-correction.
Make OCR more robust by regular expressions, e.g., by forcing five numbers and one letter in a row.
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